期刊名称：International Journal of Applied Mathematics and Computer Science
电子版ISSN：2083-8492
出版年度：2019
卷号：29
期号：2
页码：1-13
DOI：10.2478/amcs-2019-0016
出版社：De Gruyter Open
摘要：Cooperative adaptive cruise control (CACC) for human and autonomous self-driving aims to achieve active safe driving
that avoids vehicle accidents or traffic jam by exchanging the road traffic information (e.g., traffic flow, traffic density,
velocity variation, etc.) among neighbor vehicles. However, in CACC, the butterfly effect is encountered while exhibiting
asynchronous brakes that easily lead to backward shock-waves and are difficult to remove. Several critical issues should be
addressed in CACC, including (i) difficulties with adaptive steering of the inter-vehicle distances among neighbor vehicles
and the vehicle speed, (ii) the butterfly effect, (iii) unstable vehicle traffic flow, etc. To address the above issues in CACC,
this paper proposes the mobile edge computing-based vehicular cloud of the cooperative adaptive driving (CAD) approach
to avoid shock-waves efficiently in platoon driving. Numerical results demonstrate that the CAD approach outperforms
the compared techniques in the number of shock-waves, average vehicle velocity, average travel time and time to collision
(TTC). Additionally, the adaptive platoon length is determined according to the traffic information gathered from the global
and local clouds.
关键词：mobile edge computing; active safe driving; cooperative platoon driving; cooperative adaptive cruise control
